Note : Les descriptions sont présentées dans la langue officielle dans laquelle elles ont été soumises.
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FAST FOCUS ASSESSMENT SYSTEM AND METHOD FOR IMAGING
FIELD OF THE INVENTION
The present invention relates in general to focusing systems. More
particularly, the present invention relates to acquiring physical
characteristics of a human
being or animal in good focus. Even more particularly, the present invention
relates to
acquiring a focused image of an iris for iris recognition.
BACKGROUND OF THE INVENTION
Video cameras are often used to capture images of moving objects and it is
critical, inmany applications, to automatically determine when the object is
properly focused.
The focus information may be used to select a specific video frame to be saved
on some
analog or digital medium, or processed to extract certain information. The
focus information
may also be used in a feedback control mechanism to modify the parameters of
the optical
system and thereby automatically compensate for changes in object position and
keep the
image in focus.
A challenge in imaging, and particularly iris imaging, is the acquisition of
images in good focus. Several known techniques have been used for image focus
assessment.
In U.S. Patent 4,876,608, entitled "Focus and Signal to Noise Measurement
Routines in Input
Scanners", issued to Eaton, the focus of an electronic scanner is measured by
scanning a test
pattern composed of lines, and measuring the total contrast; i.e., intensity
range observed
across the line pattern. This technique is inconvenient because it requires a
special test
pattern and only measures one small area of the field of view, that where the
test pattern is
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located.
U.S.Patent5,151,583,entitled"FocusAdjustmentDeviceHavingRestrictingMeans
for Restricting a Selecting Action According to the Degree of Nearness of a
Distance
Measurement", issued to Tokunaga et al., describes the use of a separate
distance
measurement device to measure the distance to the object, compare it with the
distance to the
current plane of focus of the optical system, and adjust the focusing optics
accordingly. It
requires the use of a separate image measurement system which may not operate
fast enough
to function at video rates, and in any case must be carefully calibrated
relative to the optical
system to provide accurate focusing. U.S. Patent 5,404,163, entitled "In-Focus
Detection
Method and Method and Apparatus Using the Same for Non Contact Displacement
Measurement", issued to Kubo, describes an algorithm that uses contrast
measurements
defined as the sum of the nth power of differences in brightness between
adjoining pixels.
It assesses only localized areas and does not produce an overall assessment of
the entire
image, and methods for high speed (video-rate) implementation are not
disclosed.
When the imaging target is an iris, for the purpose of real-time personal
identification, the focusing requirement is especially challenging because of
several factors.
One factor is the small diameter of an iris (about 1 centimeter). To acquire
iris images at
reasonable distances, a long (narrow-angle) lens is required. Since the focus
depth-of-field
of a classical lens system is proportional to its angle-of-view, an iris
target will only be in
focus over a narrow range of distances.
Another factor is that the iris is a moving target. Eye movements, head
movements, and body motion of the subject are inevitable. To prevent motion
blur, the video
CCD integration time is preferably reduced or strobed. This reduction in light-
gathering
power at the imaging device leads to a lower optical F/number, and this
further reduces the
focus depth-of-field.
Yet another factor is the use of restricted wavelengths of illumination. To
minimize unpleasantness of the illumination (or even to acquire images
covertly), infrared
illumination is desirable. But the elimination of most or even all of the
visible band further
reduces the light energy available at the imaging device, and so further
decreases the optical
F/number, ~vvhich in turn reduces focus depth-of-field as above.
Still another factor is that the CCD camera gain (AGC) cannot be greatly
increased to allow for higher F/number imaging and thus greater depth-of-field
because then
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CCD noise is amplified, signal-to-noise ratio is reduced, and the
discriminable iris
information becomes more deeply buried in CCD noise.
Still further, an eye to be imaged will not be positioned initially at any
precisely specified distance (as might be achieved, for example, by use of a
chin-rest),
because of the intrusiveness and inconvenience of any such positioning device.
Therefore,
image acquisition typically begins in a state of poor focus.
Ideally, a rapid auto-focus lens should be part of an iris recognition system,
but current costs for such are prohibitive for most contemplated applications.
Iris identification systems have been developed that are capable of collecting
images of the iris and processing them to produce biometric templates. These
templates may
be used to identify individual irises with extremely low error rates, on the
order of I in 106.
The systems capture the iris images using stationary optical platforms that
are often large,
complex, and expensive. Prior art systems are difficult to use without minimal
cooperation
of the subject being identified. As a result, their usefulness in many
applications is limited.
Althoughthe artof human recognition systems is well developed, thereremain
some problems inherent in this technology, particularly the lack of a portable
or handheld
device specifically designed to solve the problems inherent in capturing a
close-up, high-
quality, properly focused image of the iris of the eye. Therefore, a need
exists for a
recognition system that overcomes the drawbacks of the prior art.
SUMMARY OF THE INVENTION
The foregoing disadvantages are overcome by a handheld imaging apparatus
which can be used to capture high-quality iris images for identification of a
person. The iris
imager includes a camera, a cold mirror, a lens, an illuminator, and a focus
assessment
processor. The imager has sensors and indicators which assist a user in
aligning and focusing
the device. The imager also automatically captures the image when proper
positioning is
achieved. The focus assessment processor accesses the image and applies
certain
measurement routines to assess the focus. The output of the focus assessment
processor is
used to control an indicator. A template representative of the iris features
is extracted and
then compared to a database of previously stored templates to identify the
person.
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BRIEF DESCRIPTION OF THE DRAWINGS
The foregoing and other aspects of the present invention will become apparent
from the following detailed description of the invention when considered in
conjunction with
the accompanying drawings. For the purpose of illustrating the invention,
there is shown in
the drawings an embodiment that is presently preferred, it being understood,
however, that
the invention is not limited to the specific methods and instrumentalities
disclosed. In the
drawings:
Fig. 1 is a schematic diagram of an exemplary iris imager in accordance with
the present invention;
Fig. 2 is a schematic diagram of an exemplary iris image recognition system
in accordance with the present invention;
Fig. 3 is a schematic diagram of an exemplary iris imager having visual and
aural indicators in accordance with the present invention;
Fig. 4 is a flow chart of a method of operation in accordance with the present
invention;
Fig. 5 is a schematic diagram of an exemplary iris image recognition system
having a focus assessment processor in accordance with the present invention;
Fig. 6 is a diagram of a power spectrum of a convolution kernel used in
accordance with the present invention;
Fig. 7 is a diaQram of the focus score versus spectral energy in accordance
with
the present invention;
Fig. 8 is a flow chart of a method of operation of focus assessment in
accordance with the present invention; and
Fig. 9 is a schematic diagram of an exemplary iris imager comprising a focus
assessment processor in accordance with the present invention.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
The present invention is directed to a focus assessment processor that can be
used with a compact, handheld imaging apparatus to capture high-quality iris
images.
Throughout the following detailed description similar reference numbers refer
to similar
elements in the figures of the drawings.
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Fi-. I illustrates a preferred embodiment of the handheld imagcr 100
constructed in accordance with the present invention. Theexemplaryhandheld,non-
invasi%-e,
non-contacting iris imager comprises an iris acquisition device 105, an
imaging lens I f ti, ,
nlirror 120, an optional diopter correction lens 125, and an illuminator 130.
The ima=r lirtr
can be powered by a standard DC or AC supply, and preferably a 9 volt battery
(not shuwn )
The iris acquisition device 105 is preferably a conventional solid state video
camera, such as a charged coupled device (CCD) or complementary metal r>\ide
semiconductor (CMOS) device. A preferred camera is a 1/3 inch format,
monochrome ('c'I)
board camera, such as a Computar model EM200 available from CBC (America)
Corhorat ion
of Commack, NY, Preferably, video camera 105 is sensitive to light of
wavelen,;ths rn ilie
range of about 400 nanometers to about 1100 nanometers, and is positioned so
that its h ont
surface coincides with the imacye plane of lens 110 in front of it. In the
prefer7ecl
embodiment, the object plane of the lens is approximately 89 mm in front of
the lens 1 1 tt.
More preferably, the lens 110 is an optical lens with approximately 14.2 mm
focal len,L~th
The mirror 120, preferably a concave cold mirror havin, a radius oi curvature
preferably about 276 mm, is disposed on the side of the lens 110 opposite
video <<rniera I (6
and creates a magnified virtual image of the iris behind mirror 120. In thc
preferred
embodiment, mirror 120 reflects visible light with wavelengths in the ran(.,,e
of about -11)1) to
about 700 nanometers, and passes light having longerwaveiengths, such as those
in the iange
of about 700 to about 900 nanometers.
The illuminator 130 is positioned just outside the edge ofthe cold mirroi 120
.urd Is
used to illuminate the iris of the subject beingidentified. The preferred i I
luminatur I 3u r.rnrts
light having wavelengths of about 680 to about 900 nanometers. Preferably, thc
illuminatc~r
130 is a miniature quartz halogen or krypton gas bulb operatini, at
approximatcf.; INvntt
The imager acquires images of an iris with sufficient clarity, focus, and size
1'0r rrse
with conventional image processing and comparison routines. A preferred image
processrng,
and comparison routine is described in U.S. Patent No. 5,291,560, "Biometr-ic
I'ersonal
Identification System Based on Iris Analysis", issued to Dausman, and commonly
assigned
with the present iiii%ention to IriScan Inc. However
any processing and comparison technique can be used with the image that is
acquiroci ar clrc
imager, such as the image pixel correlation technique described in U.S. Patent
No. 5, 572, S1r0,
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"Automated, Non-Invasive Iris Recoanition System and Method", issued to W
ildes et al. and
the techniques described in U.S. Patent No. 4,641,349, "Iris Reco,nition
System", issued tc~
Flom et al. The lens 110 gives a high resolution imaue of the eye 150 of the
user, positioned in
front of the lens 110, so that extreme proximity between the eye 150 and the
imager 100 is
not required (i.e., no contact is needed between the subject and the imager
100).
As shown in Fig. 1, imager 100 comprises a solid-state image capture device
arlcl aii
optical system which forms an image 109 of the iris on the imaLe capture
device at the iniage
plane of the video camera 105 and at the same time produces a virtual image 1
l 5 of thc iris
which the user can use to position and focus the iris image. As a result,
using the same eti-e
being imaged, a user can see a reflected image of the iris which reflected
image can he lised
to position the handheld imager 100 so that a good iris ima-e (i.e., an image
that can he
processed and compared to those stored in a database) can be obtained.
Fig). I also shows an optional dioptric correction lens -125 positioned
between the cN'e
150 and the cold mirror 120. Dioptric correction lens 125 is an adjustable
optical elenient
which corrects for the close-range focusing ability of the individual eye,
which varies fnml
subject to subject. When the lens 125 is properly adjusted, the magnified,
reflected virtual
image 115 of the subject's eye appears in sharp focus to the subject at the .
eye-to-mii-rur
distance necessary for the subject's eye to be sharply focused on the front
surface ol' tlle
camera. This simplifies use of the imager, because the subject simply
positions the image so
that the virtual image 115 of the iris appears sharply focused.
A prefecred embodiment of the dioptric correction mechanism has no correctiun
lcns
125 and instead has a mechanical means (not shown) for adjusting the position
of the cold
mirror 120 relative to the camera lens 110. This allows the user to vary the
object distance
of the cold mirror 120, thus changing the eye-to-lens distance at which the
virtual iina.:e I I
of the iris is sharply focused.
The ability to setthe dioptric correction mechanism to acconimodate a pat-
ticulau usei-
has a great utility if the imager is used by only one person inost of the
time. Once the
correction is set, the user can easily position the device to obtain a sharply
focused reflected
image. This automatically produces a sharply focused image from the camera and
substantially immediate acceptance of the image by the focus assessnient
processor desci illed
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below. Image capture time is thereby reduced and overall convenience and
utility is
enhanced.
An eye 150 is positioned in front of the imager 100 (e.g., about 3.5 inches in
front),
as shown in Fig. 1, and the illuminator 130 is turned on. This, in turn,
illuminates the eye 150
and the iris therein. Preferably, the light having wavelengths of about 400 to
about 700
nanometers is reflected by the cold mirror 120, thereby forming a magnified
virtual image
115 behind the mirror 120 which the user can see through the eye being imaged.
The radius
of curvature of the mirror is selected so that the magnified image 115 of the
eye substantially
fills the user's entire field of view. Hence, when the imager 100 is
positioned so that the
entire eye 150 is visible, it is virtually assured that the eye 150 will be
substantially centered
in the object plane 140 of the camera 105. Under these conditions, the light
having
wavelengths of about 700 to about 900 nanometers is passed by the mirror 120
and forms an
approximately centered image 109 of the eye 150 at the image plane 107 of the
camera 105.
The image is then captured and processed, as described below.
Although a cold mirror (one which reflects shorter wavelengths and passes
longer
wavelengths) is described herein, it is understood that a hot mirror (one
which reflects longer
wavelengths and passes shorter wavelengths) could also be used in accordance
with the
present invention.
The imager 100 of Fig. 1 is used in a system to identify the iris image that
has been
captured. The eye is illuminated, an acceptable or suitable image of the iris
is obtained, and
the image (or a template of the image) is compared to pre-existing images (or
to pre-existing
templates) in a memory or database for identification of the subject. The
system processes
the image and compares it to stored images (or templates) to identify the
iris, and thus, the
user. Image processing algorithms are used to extract a fixed length template
(e.g., about 512
bytes long) from each iris image. Iris images are compared by determining the
percentage
of bits in each template that match. If the percentage of bits that match
exceeds a
predetermined threshold (e.g., 75%), then it is determined that the iris
images being compared
belong to the same iris, thereby identifying the subject being tested.
Fig. 2 is a schematic diagram of an exemplary iris image recognition system in
accordance with the present invention. The imager 100 is coupled to a
microprocessor 210
that performs the processing and comparison. The microprocessor 210 can reside
in a
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conventional computer 200, such as a standard personal computer (e.g., 100
MHZ, 32 Mbyte
DRAM, monitor, keyboard, ports, hard drive, floppy drive, CD-ROM drive), as
shown, or
within an IrisEngine manufactured by IriScan Inc., Marlton, NJ.
The microprocessor 210 is coupled to the imauer 100 via conventional cables
and/or
printed circuit boards (PCBs) that are connected into slots on the computer
such as an ISA
slot or a PCI slot. Other conventional means for coupling the imager 100 and
the
microprocessor 210 can be employed, as would be understood by those skilled in
the art. The
microprocessor 210 controls the imager 100 and runs software held in read only
memory
(ROM) 205. The processor 210 is connected via a bus 207 to the ROM 205, a
random access
memory (RAM) 232, another memory such as an erasable programmable ROM (EPROM)
230, and an input/output (UO) controller 225. The RAM 232 is large enough to
hold at least
one captured image of an iris. The I/O controller 225 is connected to the
appropriate circuitry
and drivers (not shown) for issuing commands to control the imager 100.
The imager 100 preferably transmits the images in RS 170 format to a frame
grabber
PCB, such as the PixLink VGX2MB frame grabber PCB, for image processing; or
provides
the digital images directly to the processing unit 210. "On/off' data is
transmitted from the
imager 100 to the processor 210 to initiate the image acquisition function. A
digital image
could be provided if a digital camera is used. Preferably, for an analog video
camera, data
is analog RS170 from the camera 105 to the frame grabber PCB, or digital from
a digital
camera to the microprocessor 210, and digital for all other functions.
The image processing consists of a number of image processing steps (such as
those
described in U.S. Patent No. 5,291,560 and U.S. Patent No. 5,572,596, which
are herein
incorporated by reference) which lead to extraction of a unique and highly
specific digital
biometric template that can be used to identify the individual based on
intensity patterns
within the iris. The biometric template is then compared against other
templates or images
stored in a memory (such as a RAM or EPROM) 230 within the computer 200. The
memory
230 stores selected data representing images of the iris of a plurality of
subjects. A match of
the biometric template with a template stored in the memory 230 identifies the
subject whose
iris is being imaged.
Although an image of the eye is reflected back to the subject in mirror 120,
this may
not provide the desired feedback to the userto enable the user to properly
position the imager
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so that a suitable iris image is obtained. For example, a user may be a novice
in using and
positioning the imager 100 with respect to the eye 150, or the user may be
attempting to
image the eye of another subject with the imager. Thus, preferably, the imager
100 comprises
a passive feedback mechanism to guide the user in positioning the eye 150 to
an optimum
location to allow acquisition of a suitable image.
The passive feedback mechanism is an indicator or combination of indicators
that
provides, on a near real-time basis, an indication to the user that an
adequate iris image has
or has not been obtained. Fig. 3 is a schematic diagram of an exemplary iris
image
recognition system that includes position indicators in accordance with the
present invention.
Preferably, the indicator is visible and/or audible, such as, for example, an
indicator lamp 305
(e.g., a light emitting diode (LED)) that lights when an acceptable image has
been captured
(i.e., "image acquired"), and a aural indicator via a speaker 310, such as a
beep or other tone,
that sounds periodically until an acceptable image has been captured (i.e.,
"imaging in
progress").
Additional indicators 306, 307 can be also be used, either alone or in
combination, for
such indications as "subject identified - accept" and "subject not identified -
reject". These
indications would be activated pursuant to the results of the processing and
comparison
performed at the microprocessor 210, as described above with respect to Fig.
2.
The imager 100 also preferably has an on/off switch (not shown), such as a
pushbutton, for powering up the imager and initiating the image acquisition
process. Power
for the imager 100 is preferably supplied by a battery, but can also be
supplied externally,
such as, for example, from the computer 200 comprising the microprocessor 210.
The imager
100 receives and acts on instructions from the processor 210 to perform
functions such as
lighting orturning off the indicator lamp(s) 305, providing the audible
signals via the speaker
310, and lighting the 'accept' and 'reject' indicators.
It should be noted that the imagers of Figs. 2 and 3 can also contain the
optional
dioptric correction lens 125, described above with respect to Fig. 1.
Fig. 4 is a flow chart of a method of operation in accordance with the present
invention. The eye is illuminated at step 350 and an image of the iris is
obtained at step 355.
At step 360, it is determined if the image is suitable for use with the image
processing and
comparison routines. If the image is suitable, the image is passed to the
processor for further
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processing and comparison, at step 370. If the image is not suitable, at step
380, the
indicator(s) is activated (e.g., a beep sound is issued), and processing
continues at step 355
(i.e., another image is obtained).
Because the eye's own focusing system automatically adjusts to bring the
virtual
image 115 into sharp focus to the user, it cannot be relied upon to always
accurately focus the
eye image on the camera 105. For this purpose, an external focus assessment
system is used
in one embodiment, as shown in Fig. 5. Video image information from the
handheld imaging
device 100 is received as an analog video signal which conforms to a standard
format such
as NTSC or PAL. In these formats video frames are transmitted at a rate of 25
(PAL) or 30
(NTSC) frames per second. The analog image data is transmitted to an analog-to-
digital
converter 405 and stored in a frame buffer memory 410, such as a RAM similar
to RAM 232
described above with respectto Fig. 2, and capable of storing one complete
frame of digitized
video information. A focus assessment processor 420 accesses the digitized
image
information and applies certain measurement routines which are described
below. The output
of the focus assessment processor 420 is used to control an indicator, such as
the audible
indicator 310. As long as the focus assessment processor 420 determines that
the captured
image is not acceptable for further processing and comparison, the audible
indicator 310 is
directed to emit periodic sounds to alert the user. Images are repeatedly
acquired and
assessed until an acceptable one is received. After an acceptable iris image
has been received,
the audible indicator 310 is turned off and the final image is retained for
further processing
and comparison, for example, by the microprocessor 210, as described above.
With respect to the preferred system and method for focus assessment in
accordance
with the present invention, a focus score is computed for each video frame (i.
e., each captured
image). If the focus score exceeds a predetermined value, then it is
determined that the image
is focused enough for further processing and comparison. If the focus score
does not exceed
the predetermined value, then it is determined that the image is not focused
enough for further
processinQ, and an indicator (such as indicator 3 10, described with respect
to Fig. 3) is
activated and a further image is captured. Alternatively, a sequence of image
frames can be
obtained that cycle through a range of focus distances strobed at the video
frame-rate, and the
focus score computed for each frame can enable the selection of the best
focused frame within
the sequence of frames. For example, by obtaining image frames at each of
several different
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lens settings and then fitting a spline curve to their respective focus scores
one can predict the
lens position that would deliver substantially the sharpest focus, by setting
the derivative of
the parameterized spline curve to zero and then solving the equation for
position.
Specific implementation features of the preferred focus assessment system and
method
which enable its real-time operation, include (1) the computation of
quantities in the 2D
Fourier domain, without needing to compute an actual 2D Fourier Transform of
an image
(this avoids the need for approximately 2.25 million floating-point operations
required for an
FFT (Fast Fourier Transform) on a 500 x 500 pixel image, as the computational
complexity
of an FFT on n x n data is O(n2log2n)); (2) only 6,400 integer multiplications
(squarings) are
performed, which in turn can be eliminated altogether by using small look-up
tables; (3) no
floating-point operations are used; (4) computation of focus scores is based
upon simple
algebraic combinations of pixel values within local closed neighborhoods,
repeated across
regions of the image; and (5) these operations not only allow the algorithm to
execute in real-
time, but also enable a straightforward implementation in simple, low-cost,
hardware devices
that could be embedded within a digital camera or frame grabber.
Preferably, the focus assessment processor 420 is fast enough to determine a
focus
score for each frame in a video image stream in less than the time it takes to
acquire a new
frame (e.g., approximately 25 ms). The frame-by-frame focus scores can be used
to control
a moving lens element for rapid and accurate focus control, or alternatively,
to select which
of several frames in a video stream is the one in best focus. The rapid
selection of well-
focused video frames for further processing, such as image analysis and
pattern recognition,
is important in real-time computer vision because it prevents wasting
processing time on
poorly-focused images.
The preferred focus assessment processor measures the focus quality of video
images
at standard rates of 25 (PAL) or 30 (NTSC) frames per second.
It is contemplated that the focus assessment processor 420 can be implemented
in a
general purpose personal computer or by a dedicated, low cost processor which
is small
enough to be incorporated into the camera electronics.
The processing of a video frame results in the return of an integer value
(e.g., on a
scale between 0 and 100) reflecting the quality of focus; the larger the value
of the integer,
the better the focus. A value of 0 indicates a completely defocused image
whereas the value
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of 100 indicates maximum focus quality. A predetermined threshold is used to
determine
whether an image is sufficientlv focused or whether another image needs to be
retrieved. For
example, values greater than about 40 can indicate sufficient quality of focus
to warrant
further image processing, while values less than about 40 cause a new image
frame to be
grabbed, and optional feedback provided to the focusing mechanism, if one
exists, or to the
subject controlling the camera position (via the indicator 310, for example).
Optical defocus is a phenomenon of the 2D Fourier domain. An image represented
as a 2D function of the real plane, I(r,)), has a 2D Fourier Transform F(,u,
) defined as shown
in equation 1.
F( ,v)- ~ ~Yj(x>Y)e 't'"xt'~'1dx~?'Y (1)
(2~)
In the image domain, defocus is preferably represented as convolution by the
2D point-spread
function of the defocused optics. This in turn may be modeled as a Gaussian
whose space
constant is proportional to the degree of defocus. Thus, for perfectly focused
optics, the
optical point-spread function shrinks almost to a delta function, and
convolution with a delta
function causes no change to the image. Progressively defocused optics equates
to
convolving with a wider and wider point-spread function, which averages
together whole
neighborhoods of pixels by such a weighting function, thereby producing an
increasingly
blurred image.
If the convolving optical point-spread function causing defocus is modeled as
a
Gaussian whose width represents the degree of defocus, then defocus is
equivalent to
multiplying the 2D Fourier Transform of a perfectly focused image with the 2D
Fourier
Transform of the "defocusing" (convolving) Gaussian. This latter quantity is
itself just
another 2D Gaussian but in the Fourier domain, and its space constant (6) is
the reciprocal
of that of the image-domain convolving Gaussian that represented the optical
point-spread
function. The preferred focus assessment processor uses (1) the duality of
convolution and
multiplication in the two domains; (2) the fact that a Gaussian has a Fourier
Transform which
is itself a Gaussian, but with the reciprocal width because of (3) the
Similarity Theorem.
Thus, the 2D Fourier Transform DJ ,v) of an image defocused to degree 6 is
related to
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F( ,u), the 2D Fourier Transform of the corresponding in-focus image, as given
by equation
2.
_ Z+v2/
D6(l~,v) e F(ta>v) (2)
From the above equation, the effect of defocus is to attenuate primarily the
highest
frequencies in the image, and that lower frequency components are virtually
unaffected by
defocus since the exponential term approaches unity as the frequencies ( ,v)
become small.
For simplicity, the present description has assumed isotropic optics and
isotropic blur, and the
optical point-spread function has been described as a Gaussian. However, the
analysis can
readily be generalized to non-Gaussian and to anisotropic optical point-spread
functions, as
would be understood by those skilled in the art.
Thus, an effective way to estimate the quality of focus of an image is to
measure its
total amount of energy in the 2D Fourier domain at high spatial frequencies,
since these are
the most attenuated by defocus. One may also perform a kind of "contrast
normalization" to
make such a spectrally-based focus measure independent of image content, by
comparing the
ratio of energy in the highest frequency bands to that in slightly lower
frequency bands. Such
spectrally-based energy measurements are facilitated by exploiting Lord
Rayleigh's theorem
for conserved total power in the two domains, shown in equation 3.
J-~ J--II(xY) 12 dxdY= f . f MT IF( ,v) 12d dv (3)
Thus, high-pass filtering or band-pass filtering an image at a ring of high
spatial frequency
(using only convolution in the 2D image domain) and measuring the residual
energy, is
equivalent to making the corresponding energy measurement in the high
frequency bands of
the 2D Fourier domain. The appropriate measurements in the 2D Fourier domain
to assess
focus can be performed without computing a time-consuming 2D Fourier
Transform. Indeed,
the measurements can be performed without even a single floating-point
operation, and even
without anv multiplications if appropriate convolution kernels and look-up
tables are used.
A real-time procedure for focus assessment based on these principles is used
in the
focus assessment processor 420. It executes much faster than the video frame-
rate, and so
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real-time focus assessments can be made on a frame-by-frame basis. These can
be used either
to control the position of a focusing lens element, or alternatively as a type
of autofocus
system in which frames are grabbed at a variety of focal depths in order to
select only the best
one for processing, or to prevent time being wasted on processing image frames
which are
assessed to be in poor focus.
The 2D spectral measurements described above can be implemented by convolving
an image with the following convolution kernel, in which pixel values within a
predetermined
region, such as, for example, an (8 x 8) neighborhood, are added together with
the weights
indicated in each of the cells:
-1 -1 -1 -1 -1 -1 -I -1
-1 -1 -1 -1 -1 -1 -1 -1
-1 -1 +3 +3 +3 +3 -1 -1
-1 -1 +3 +3 +3 +3 -1 -1
-1 -1 +3 +3 +3 +3 -1 -1
-1 -1 +3 +3 +3 +3 -1 -1
-1 -1 -1 -1 -1 -1 -1 -1
-1 -1 -1 -1 -1 -1 -1 -1
It should be noted that no pixel-by-pixel multiplications are needed in order
to impose these
weights. Rather, the pixels in the central region are added together, such as
the (4 x 4) square,
that sum is tripled, and then all pixel values in the outer two pairs of rows
and columns are
subtracted from the tripled sum. The result is squared and added to an
accumulator, thus
implementing the left-hand side of equation (3) above for this local region of
the image. The
complete (8 x 8) convolution kernel is then moved to a new position in the
image, along a
sampling grid that selects every 4th row and every 4th column, and the
operation is repeated.
Thus, to assess the quality of focus within the central (320 x 320) region of
an image, this set
of 64 pixel summations followed by a squaring operation is repeated a total of
(320/4)2 =6,400
times.
In the 2D Fourier domain, the spectral consequences of this operation can be
appreciated by examining the 2D Fourier Transform of the convolution kernel
above. The
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kernel is equivalent to the superposition of two centered square box
functions, one of size (8
x 8) and amplitude -1, and the other of size (4 x 4) and amplitude +4 (for the
central region
in which they overlap, the two therefore sum to +3). The 2D Fourier Transform
of each of
these square functions is a 2D "sinc" function, whose size parameters differ
by a factor of two
in each of the dimensions and whose amplitudes are equal but opposite, because
the two
component boxes have equal but opposite volumes. Thus, the overall kernel has
a 2D Fourier
Transform K( ,u) which is the difference of two differently-sized 2D sinc
functions, as given
by equation 4.
K( ,v)= sin( )sin(v) sin(2 )sin(2v) (4)
71Z v 47C2 v
The square of this function of g and v in the 2D Fourier domain is plotted in
Fig. 6,
showing K2(g,v), the convolution kernel's 2D power spectrum. This is a high-
pass (or
ultimately a band-pass) filter, selecting only a high range of spatial
frequencies in all
orientations. Towards its center, corresponding to very low spatial
frequencies, its value
approaches zero (as can also be inferred from the fact that the sum of all
pixel weights in the
convolution kernel shown above is zero). Thus, low frequencies play little or
no role in
computing a focus score, and only relatively high frequencies contribute
significantly to the
computation of a focus score. Equation (3) shows that summing the squares of
all the local
convolution sums across the image is equivalent to summing the total amount of
high
frequency energy in the 2D Fourier Transform of the image. The action of the
convolution
kernel is to impose the above power spectral weighting function so that
primarily high
frequency energy is measured.
The summated 2D spectral energy is then passed throu(y,,h a compressive
nonlinearity
of the form f(x)=100 x2/(xz+c2) in order to generate a normalized focus score
in the range of
0 to 100 for any image. Fig. 7 shows a diagram of the focus score versus
spectral energy in
accordance with the present invention.
The focus assessment technique is applied immediately after each image frame
is
digitized and stored in the frame buffer memory 410 in order to assess whether
the focus
quality is sufficient to warrant any further processing. If the calculated
focus quality value
of the captured image is greater than or equal to a predetermined value, the
image is passed
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to applicable programs for further processing, for example for extraction of a
biometric
template. The focus assessment technique can be used to compare the relative
focus of an
entire series of images in order to select the one most in-focus (i.e., having
the highest focus
assessment score), as well as to measure a single image.
The focus assessment technique can be used to provide a feedback indication to
a
system user who controls the position of the imager relative to the object
being imaged. This
can be accomplished by activating an indicator which would continue, while
successive
images are captured and their focus assessed, until the focus assessment score
exceeds a
predetermined value. At this point, the indicator is deactivated and the last
image captured
is transferred to the image processor 210 where it is processed to extract the
biometric
template.
The application of the focus assessment technique in combination with the
feedback
indicator helps resolve the man-machine interface problems associated with the
use of digital
imaging devices on the eye. Individuals using the system are provided
positive, objective
indicators and feedback as to the quality of image focus. The focus assessment
processor can
also be used in any situation where it is required to determine the quality of
focus of video
images at industry standard frame rates (NTSC and PAL).
Fig. 8 is a flow chart of an exemplary method of operation of focus assessment
in
accordance with the present invention. At step 600, an image is obtained at
the imager and
transmitted to an analog to digital converter 405. The digitized video
information is then
stored in a frame buffer memory 410. At step 605, the focus assessment
processor 420
isolates the central region (e.g., 320 x 320 pixels) of the image. Pixel
blocks (e.g., 8 x 8
blocks, with each pixel being in only one block) are then processed by first
summing pixels
in the central region (e.g., 4 x 4), at step 610. The outer pairs of rov'-s
and columns are then
summed, at step 615, and are combined in a predetermined ratio, such as 1:-3
with the central
region pixel blocks, at step 620. In other words, for example, the sum from
step 610 is
tripled, and then all the pixel values in the outer two pairs of rows and
columns from step 615
are subtracted from this value. This result is then squared, at step 625. This
process is
performed on each 8 x 8 block, and the results are summed. After the entire
image has been
processed, at step 630, the summed result is compressed nonlinearly. at step
635, to generate
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a focus score, preferably between 0 and 100. This score is then compared to a
predetermined
number for determining if the indicator 310 should be activated, at step 640.
The focus assessment can be performed by the microprocessor 210 in the
computer
200, or it can be a separate processor element. For example, the focus
assessment processor
420 can be disposed within the handheld imager 100, as shown in Fig. 9, and
not be external
to the imager 100, as shown in Fig. 5. A benefit of this embodiment is that
the selection of
a properly focused image can occur within the hand-held device, so that only a
single,
acceptable image is transmitted to the external processor 210. In the
embodiment shown in
Fig. 5, the focus assessment method is typically performed within a personal
computer, so
digitized image data is transmitted to the personal computer at video rates.
However, the high
data rates associated with transmission of digitized video cannot be supported
by some types
of computers, particularly notebook-style personal computers. If the focus
assessment is
performed in the handheld device 100, the single selected video frame can then
be transmitted
at a lower data rate which is compatible with notebook-style personal
computers. This greatly
enhances the flexibility and versatility of the handheld imaging device of the
present
invention.
As shown in Fig. 9, the video signal (analog) from the camera 105 is converted
to
digital format by an analog-to-digital converter 405 and each frame of video
is stored in a
frame buffer memory 410. The converter 405 and memory 410 are similar to those
described
above with respect to Fig. 5, but are disposed within the handheld imager 100.
Data in the
frame buffer 410 is processed by a focus assessment processor 420 which is
also contained
within the handheld imager 100. The results of the focus assessment control an
audible
indicator 310 which emits a sound that is discontinued when an acceptable
video frame is
acquired. The single video frame that has been determined to be acceptable is
transmitted to
another processor 210 (typically within a personal computer 200) for further
processing and
comparison.
It is contemplated that in addition to the focus assessment processor, an auto-
focus
lens system could be used in the present invention. The results of the focus
assessment
control the lens system, thereby automatically adjusting focus to produce an
optimal image.
This would place less of a premium on the accuracy with which the user
positions the eye,
and would be helpful if the user could not see or hear the indicators
described above.
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Optionally, the imager of the present invention can be equipped with a
display, such
as a miniaturized back-illuminated liquid crystal display (LCD) 505. The LCD
display 505
is disposed on the side of the imaging system opposite the subject whose eye
is being imaged.
The video signal generated by the camera 105 is continuously displayed on the
LCD display
505 to permit an operator (other than the subject whose eye is being imaged)
to control the
position of the hand-held imaging device 100 and thereby center the eye's
image in the field
of view to more easily achieve proper focus, as indicated by the sound emitted
by the audible
indicator 310. This allows the device to be used on individuals who are unable
or unwilling
to cooperate in the image acquisition process. Thus, in accordance with the
present invention,
either a user can scan his own iris (e.g., for entry to a building) or a user
can scan another
subject's iris (e.g., for identification).
Although the present invention is described within the context of imaging the
iris of
the eye for the purpose of extraction of template information for biometric
identification, it
is contemplated that focus assessment processor and method of the present
invention can be
used in any other application where quick focus is desired. Moreover, the
focus assessment
processor and method of the present invention can be used in any imaging
device, not only
a handheld imaging device.
Although illustrated and described herein with reference to certain specific
embodiments, it will be understood by those skilled in the art that the
invention is not limited
to the embodiments specifically disclosed herein. Those skilled in the art
also will appreciate
that many other variations of the specific embodiments described herein are
intended to be
within the scope of the invention as defined by the following claims.
